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Record W2956133108 · doi:10.5287/ora-nbd1ym74j

Essays on corporate taxation

2017· dissertation· en· W2956133108 on OpenAlexaboutno aff
Katarzyna Habu

Bibliographic record

VenueOxford University Research Archive (ORA) (University of Oxford) · 2017
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Taxation and Avoidance
Canadian institutionsnot available
Fundersnot available
KeywordsTaxable incomeMultinational corporationSubsidiaryBusinessCorporate taxTax avoidanceLeverage (statistics)AccountingMonetary economicsDouble taxationFinanceEconomics

Abstract

fetched live from OpenAlex

This thesis aims to advance our understanding of corporate taxes and their effects on firm behaviour, particularly with regard to tax avoidance and investment, as well as how countries fight tax evasion and avoidance. Each chapter provides a distinct contribution to the corporation tax literature. The first two chapters analyze the corporate tax payments of companies residing in the United Kingdom using confidential corporate tax returns data. Chapter 1 focuses on comparisons between various company-ownership types, distinguishing in particular between multinational and domestic companies. I find that multinational companies, in spite of constituting only 3 percent of the population of UK companies, pay the majority of UK corporation tax, around 55 percent on average, during the period 2000 - 2011. However, multinational companies pay a very small amount of tax relative to their size, in comparison to domestic companies, and the share of UK corporation tax paid by multinational companies has declined over the period. Chapter 2 shows that there are systematic differences in how much taxable profits multinational and domestic companies report. Specifically, using comparable samples selected by propensity score matching, I estimate that UK subsidiaries of foreign multinationals report a 50 percent lower ratio of taxable profits to total assets than comparable domestic standalones. This difference is almost entirely attributable to the fact that a higher proportion of foreign multinational subsidiaries report zero taxable profits (59.2 percent) than domestic standalones (27.5 percent). A high share of foreign multinational subsidiaries are found to report zero taxable profits persistently over time, and high leverage is found to play an important role in producing this outcome. This suggests a very aggressive form of profit shifting for many of these foreign multinational companies. Chapter 3 investigates how investment responds to tax incentives. In particular, using the announcement and subsequent implementation of an exogenous tax reform in Canada as a quasi-natural experiment, I consider the effect of a temporary and unexpected increase in the cost of capital for a group of firms (income trusts) which had (for tax reasons) limited availability of retained earnings as a source of finance for investment. I show that these firms did not respond to the cost of capital increase during the period when they had limited availability of retained earnings. In turn, a subsequent increase in the availability of internal finance, prompted by the implementation of the tax reform in 2011, is shown to increase their investment substantially. These findings suggest that financing constraints on investment may have been binding for these firms. Chapter 4 discusses the exchange of tax information between tax havens and OECD countries. Together with Clemens Fuest, we analyze how tax havens have chosen their partner countries to sign tax information exchange agreements (TIEAs) with and hence comply with OECD standards. We find that tax havens have on average signed more TIEAs with countries to which they have stronger economic links. However, this does not mean that they exchange tax information with all important partner countries.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.003
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0190.006

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.048
GPT teacher head0.259
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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